A Cognitive Anycast Routing Method for Delay-Tolerant Networks

Abstract

A cognitive networking approach to the anycast routing problem for delay-tolerant networking (DTN) is proposed. The method is suitable for the space–ground and other domains where communications are recurrently challenged by diverse link impairments, including long propagation delays, communication asymmetry, and lengthy disruptions. The proposed method delivers data bundles achieving low delays by avoiding, whenever possible, link congestion and long wait times for contacts to become active, and without the need of duplicating data bundles. Network gateways use a spiking neural network (SNN) to decide the optimal outbound link for each bundle. The SNN is regularly updated to reflect the expected cost of the routing decisions, which helps to fine-tune future decisions. The method is decentralized and selects both the anycast group member to be used as the sink and the path to reach that node. A series of experiments were carried out on a network testbed to evaluate the method. The results demonstrate its performance advantage over unicast routing, as anycast routing is not yet supported by the current DTN standard (Contact Graph Routing). The proposed approach yields improved performance for space applications that require as-fast-as-possible data returns.